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This research advances quantum computational complexity by extending the Quantum Max Cut framework from qubits to higher-dimensional qudits. By leveraging the algebraic structure of swap operators and representation theory, the team bypasses the exponential scaling typical in quantum simulations to derive exact analytical solutions for specific network topologies. This methodological shift offers a more efficient pathway for solving hard graph problems using noncommutative polynomial optimization.
Qudits and Swap Operators Solve Hard Graph Problem

This paper investigates the algebraic structure of a higher-dimensional analog of the Quantum Max Cut (QMC) problem for systems of qudits. The Quantum Max $d$-Cut ($d$-QMC) problem asks for the largest eigenvalue of a Hamiltonian on a graph with $n$ vertices whose edges correspond to swap operators acting on $(\mathbb C^d)^{\otimes n}$.
Igor Klep of the University of Ljubljana, Tea Štrekelj of the University of Primorska, and Jurij Volčič of the University of Auckland report a new approach to solving a complex computational problem using systems of qudits, a higher-dimensional analog of qubits. The researchers identified the algebra generated by swap operators as a quotient of a free algebra, defined by symmetric group relations plus a single additional relation of degree d. This…
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